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EDUC 200C Section 1– Describing Data

EDUC 200C Section 1– Describing Data. Melissa Kemmerle September 28, 2012. First things…. Hi, I’m Melissa 3 rd year CTE student, math education Goal of section this quarter Keep material as painless as possible Present some new material as necessary

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EDUC 200C Section 1– Describing Data

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  1. EDUC 200CSection 1– Describing Data Melissa Kemmerle September 28, 2012

  2. First things… • Hi, I’m Melissa • 3rd year CTE student, math education • Goal of section this quarter • Keep material as painless as possible • Present some new material as necessary • Review and answer questions about class concepts and problem sets Questions, comments, or concerns?

  3. Today’s Goals • Discuss mean, variance, standard deviation • Look at Hands data • Introduce z-scores • Briefly introduce correlation • Answer any homework questions

  4. How do we describe data? • Measures of “central tendency” and measures of “spread”

  5. Measures of Central Tendency Mode, Median, Mean…

  6. The mode The mode is the score with the highest frequency of occurrences. It is the easiest score to spot in a distribution. It is the only way to express the central tendency of a nominal level variable.

  7. The median The median is the middle-ranked score (50th percentile). If there is an even number of scores, it is the arithmetic average of the two middle scores. The median is unchanged by outliers. Even if Bill Gates were deleted from the U.S. economy, the median asset of U.S. citizens would remain (more or less) the same.

  8. The Mean • We’ll most commonly use the mean

  9. Visualizing the Mean

  10. Measures of Spread • Variance, standard deviation • Why do we care about spread?

  11. Deviation score • Measure the distance of each point from the mean

  12. How do we summarize this? • Could use “mean deviation” • But the sum of deviation scores will always be 0 (why?), thus mean deviation will always be 0 • What about mean absolute value of the deviation? • This will guarantee a positive sum of deviation scores, but has undesirable properties for more advanced statistics

  13. Variance and Standard Deviation • The answer is to take the average of the squared deviation scores • This is called the variance • Hard to interpret—still in “squared deviation” units • Standard deviation is the square root of the variance • Gives a measure of deviation in the units of the original observations • Note the N-1 is used to correct bias in estimates of sample standard deviation and variance

  14. Calculating Mean and SD • It’s probably a good idea to do it by hand once or twice. • After that, you can use Excel. • Let’s look at our hands data. • Calculate mean and SD for each cohort’s hands data. Which cohort is best at estimating hand size? How can we tell?

  15. Z-scores • We can transform data about different variables to the same scale by creating z-scores • This makes it easier to compare variables • Z-scores always have a mean of 0 and standard deviation of 1

  16. Correlation • Correlation is used to describe how two variables vary with each other • What are some examples of variables that might have positive or negative or zero correlation?

  17. Z-scores don’t change correlation

  18. Questions?

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